Characterization of different component processes of photosynthesis is useful to understand the growth status of plants and to discover possible unintended effects of genetic modification on photosynthesis in transgenic plants. We focused on the changes in photosynthetic gas-exchange properties, reflectance spectra, and plant growth traits among groups of different transgenic barley T1 (TolT1) and its isogenic controls (TolNT1), TolT1, and group of its own transgenic progenies T2 (TolT2), TolNT1 and its wild type (WT), respectively. Gas-exchange measurements showed that only the net photosynthetic rate (P N) and the light-use efficiency (LUE) differed significantly between TolT1 and TolT2 with no obvious changes of other characteristics. Reflectance measurements indicated that the reflectance ratio was sensitive to identify the differences between two barley groups. Differences in reflectance expressed on an index basis depended on barley groups. The relationship between LUE and the photochemical reflectance index (PRI) at a leaf level among different barley groups of WT, TolNT1, TolT1 and TolT2 did not changed obviously. The differences in the total leaf area per plant (LA) between WT and TolNT1 as well as between TolT1 and TolT2 were significant. This study finally provided a plausible complex explanation for the unintended effects of genetic transformation on photosynthesis-related properties in barley at different levels. Furthermore, it was concluded that the photosynthesis-related properties of transgenic plants based on gas exchange, leaf reflectance, and plant growth measurements responded to the same environment in a more different way between two subsequent generations than to the processes of the gene insertion by Agrobacterium and associated tissue culture., C. X. Sun ... [et al. ]., and Obsahuje bibliografii
A universal set of equations for determining chlorophyll (Chl) a, accessory Chl b, c, and d, and total Chl have been developed for 90 % acetone, 100 % methanol, and ethanol solvents suitable for estimating Chl in extracts from natural assemblages of algae. The presence of phaeophytin (Ph) a not only interferes with estimates of Chl a but also with Chl b and c determinations. The universal algorithms can hence be misleading if used on natural collections containing large amounts of Ph. The methanol algorithms are severely affected by the presence of Ph and so are not recommended. The algorithms were tested on representative mixtures of Chls prepared from extracts of algae with known Chl composition. The limits of detection (and inherent error, ±95 % confidence limit) for all the Chl equations were less than 0.03 g m-3. The algorithms are both accurate and precise for Chl a and d but less accurate for Chl b and c. With caution the algorithms can be used to calculate a Chl profile of natural assemblages of algae. The relative error of measurements of Chls increases hyperbolically in diluted extracts. For safety reasons, efficient extraction of Chls and the convenience of being able to use polystyrene cuvettes, the algorithms for ethanol are recommended for routine assays of Chls in natural assemblages of aquatic plants.
Parsing models for all Universal Depenencies 1.2 Treebanks, created solely using UD 1.2 data (http://hdl.handle.net/11234/1-1548).
To use these models, you need Parsito binary, which you can download from http://hdl.handle.net/11234/1-1584.
Tokenizer, POS Tagger, Lemmatizer and Parser models for all Universal Depenencies 1.2 Treebanks, created solely using UD 1.2 data (http://hdl.handle.net/11234/1-1548).
To use these models, you need UDPipe binary, which you can download from http://ufal.mff.cuni.cz/udpipe.
Tokenizer, POS Tagger, Lemmatizer and Parser models for all 50 languages of Universal Depenencies 2.0 Treebanks, created solely using UD 2.0 data (http://hdl.handle.net/11234/1-1983). The model documentation including performance can be found at http://ufal.mff.cuni.cz/udpipe/users-manual#universal_dependencies_20_models .
To use these models, you need UDPipe binary version at least 1.2, which you can download from http://ufal.mff.cuni.cz/udpipe .
In addition to models itself, all additional data and value of hyperparameters used for training are available in the second archive, allowing reproducible training.
Tokenizer, POS Tagger, Lemmatizer and Parser models for 123 treebanks of 69 languages of Universal Depenencies 2.10 Treebanks, created solely using UD 2.10 data (https://hdl.handle.net/11234/1-4758). The model documentation including performance can be found at https://ufal.mff.cuni.cz/udpipe/2/models#universal_dependencies_210_models .
To use these models, you need UDPipe version 2.0, which you can download from https://ufal.mff.cuni.cz/udpipe/2 .
Tokenizer, POS Tagger, Lemmatizer and Parser models for 131 treebanks of 72 languages of Universal Depenencies 2.12 Treebanks, created solely using UD 2.12 data (https://hdl.handle.net/11234/1-5150). The model documentation including performance can be found at https://ufal.mff.cuni.cz/udpipe/2/models#universal_dependencies_212_models .
To use these models, you need UDPipe version 2.0, which you can download from https://ufal.mff.cuni.cz/udpipe/2 .
Tokenizer, POS Tagger, Lemmatizer and Parser models for 84 treebanks of 56 languages of Universal Depenencies 2.3 Treebanks, created solely using UD 2.3 data (http://hdl.handle.net/11234/1-2895). The model documentation including performance can be found at http://ufal.mff.cuni.cz/udpipe/models#universal_dependencies_23_models .
To use these models, you need UDPipe binary version at least 1.2, which you can download from http://ufal.mff.cuni.cz/udpipe .
In addition to models itself, all additional data and value of hyperparameters used for training are available in the second archive, allowing reproducible training.
Tokenizer, POS Tagger, Lemmatizer and Parser models for 90 treebanks of 60 languages of Universal Depenencies 2.4 Treebanks, created solely using UD 2.4 data (http://hdl.handle.net/11234/1-2988). The model documentation including performance can be found at http://ufal.mff.cuni.cz/udpipe/models#universal_dependencies_24_models .
To use these models, you need UDPipe binary version at least 1.2, which you can download from http://ufal.mff.cuni.cz/udpipe .
In addition to models itself, all additional data and value of hyperparameters used for training are available in the second archive, allowing reproducible training.
Tokenizer, POS Tagger, Lemmatizer and Parser models for 94 treebanks of 61 languages of Universal Depenencies 2.5 Treebanks, created solely using UD 2.5 data (http://hdl.handle.net/11234/1-3105). The model documentation including performance can be found at http://ufal.mff.cuni.cz/udpipe/models#universal_dependencies_25_models .
To use these models, you need UDPipe binary version at least 1.2, which you can download from http://ufal.mff.cuni.cz/udpipe .
In addition to models itself, all additional data and value of hyperparameters used for training are available in the second archive, allowing reproducible training.